How Machines and People Learn, Compete, and Evolve With Dr. Una-May O’Reilly

Dr. Una-May O’Reilly of MIT CSAIL talks about how we can better understand machine learning by looking at the evolution of intelligence itself, and tells us how that understanding informs her work in applying artificial intelligence techniques to counter cybersecurity threats.

Dr. Una-May O'Reilly is the Leader and Principal Research Scientist of Anyscale Learning For All (ALFA) Group at MIT CSAIL. ALFA focuses on scalable machine learning, evolutionary algorithms, and frameworks for large-scale knowledge mining, prediction and analytics. ALFA conducts research in artificial adversarial intelligence- related to cybersecurity, MOOC data analytics, and data-driven medical modeling. Una-May has expertise in agile data science systems with rapid intelligent data analytics capabilities.

Una-May received the EvoStar Award for Outstanding Achievements in Evolutionary Computation in Europe in 2013. She is recognized by ACM SIG-EVO for her significant contributions having been elected a Fellow of ISGEC; serves as Vice-Chair of ACM SIG-EVO, and has served as chair of the largest international Evolutionary Computation Conference, GECCO. She has served on the GECCO business committee, co-led the 2006 and 2009 Genetic Programming: Theory to Practice Workshops and co-chaired EuroGP, the largest conference devoted to Genetic Programming.